The role of public online information in helping to reduce disaster damage is expected to become increasingly important since it can be used for decision making about disaster response. This paper aims to discuss the effectiveness and limitations of real-time online information about heavy rainfall based on an analysis of data on the disaster caused by Typhoons 17 and 18 in 2015 in Miyagi prefecture, Japan, and on a focus group interview survey with four experts on natural disasters. The results from the interviews showed the following: (1) Landslide alert information is reliable for prediction purposes. However, many people did not monitor it because it was released around midnight. (2) Areas of landslide occurrence and river flooding correspond to areas with heavy cumulative rainfall. Yet cumulative rainfall data are not available on the web. (3) The available radar-rainfall data can be used to predict the situation one hour from the present as long as the person has expert knowledge. (4) It is possible to monitor river water levels at many points. Yet, about half of the observation points have no established “flood danger water level.” (5) Local governments released a great amount of disaster information through social media before flooding occurred on some rivers. However, one must monitor multiple social media accounts and not just the account of one’s hometown.
Validation of Real-Time River Flow Forecast Using AWS Rainfall Data
